Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "54"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 54 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 33 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 31 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 54, Node N04:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459848 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 13.290354 0.505495 29.735184 -0.618168 14.331254 2.109279 2.330787 3.996132 0.0512 0.7603 0.5574 1.473381 3.075815
2459847 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 15.366130 -0.442216 27.761044 -0.414620 21.827506 1.858237 0.797086 1.449361 0.0423 0.6991 0.5303 1.404662 2.581382
2459846 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 24.867707 -1.075278 33.721827 -0.007132 21.664346 1.615530 4.256981 -0.512638 0.0459 0.7071 0.4789 1.610311 3.064664
2459845 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 16.905537 -0.315897 39.432344 0.139502 10.115741 -0.204663 1.564699 0.307908 0.0590 0.7636 0.6514 1.174578 9.984699
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - 13.915515 0.504969 5.904540 0.152813 0.808160 0.454357 6.230232 1.493963 0.0517 0.0740 0.0234 nan nan
2459843 digital_ok 100.00% 100.00% 0.66% 0.00% 100.00% 0.00% 17.085871 -0.975150 19.115369 -1.175527 64.463905 0.196363 0.231233 1.592351 0.0521 0.7625 0.6212 1.696072 4.048418
2459838 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 67.892118 84.055899 71.443569 66.768911 68.429362 67.519417 772.492363 591.556943 0.0168 0.0165 0.0004 0.000000 0.000000
2459833 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.845383 -0.789290 0.815562 0.569532 -0.544486 0.352991 0.432844 1.390399 0.0433 0.0932 0.0053 nan nan
2459832 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.596226 11.433258 0.992896 -0.579345 0.533210 9.220807 0.789468 1.014506 0.0926 0.0925 0.0187 1.224004 1.224971
2459831 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.531910 -0.549216 -1.052095 1.343212 -0.668479 -0.895905 -0.206040 0.774682 0.0355 0.0424 0.0016 nan nan
2459830 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.580126 22.870577 1.387894 1.288152 0.789526 5.660819 1.275403 2.703064 0.0846 0.0967 0.0208 1.241719 1.240192
2459829 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.887994 35.378165 1.133631 1.168500 0.949517 4.816593 1.734312 2.038527 0.0940 0.1021 0.0179 34.971879 22.095003
2459828 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.866973 11.643199 1.028494 1.823077 0.059000 3.400357 2.502953 0.119643 0.0762 0.0898 0.0169 1.252671 1.250877
2459827 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.465320 26.744552 1.336424 1.512398 0.645341 3.833578 0.127570 0.623499 0.0946 0.1034 0.0191 1.202207 1.199721
2459826 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.357972 15.447347 1.626663 2.287286 1.295870 5.727232 0.563729 -0.082438 0.0664 0.0721 0.0119 1.147168 1.135188
2459825 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.595436 6.352998 1.364107 0.424943 -0.965889 7.217102 -0.584822 15.917780 0.0784 0.0945 0.0182 1.194300 1.189275
2459824 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.568712 28.965965 1.229012 0.985292 0.224002 2.603130 1.311546 0.107834 0.1073 0.1165 0.0202 1.216093 1.215526
2459823 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.168314 6.588890 1.941136 3.457562 0.094130 3.290488 2.220261 1.683441 0.0955 0.1055 0.0220 1.132707 1.129892
2459822 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.914717 8.403356 1.392426 3.117768 -0.513406 5.749390 0.976564 7.216219 0.0889 0.0948 0.0182 1.199499 1.192283
2459821 digital_ok 100.00% 11.29% 11.29% 0.00% 100.00% 0.00% 1.481911 1.898634 1.325956 1.798883 -1.375839 3.371661 0.215494 24.437464 0.7373 0.6010 0.4247 4.016303 3.281438
2459820 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.443531 2.954496 1.131213 1.142228 0.300717 11.202453 0.492268 4.520073 0.7864 0.7070 0.3933 4.245019 3.731064
2459817 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 50.00% 0.837481 -0.306333 1.319126 1.057010 -0.334606 -0.447355 -0.254084 -0.719210 0.8326 0.7109 0.4779 2.826214 2.688585
2459816 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.657856 -0.685763 1.846962 0.832313 0.967530 1.487681 1.246738 -0.570147 0.8500 0.6262 0.5662 1.911709 1.596301
2459815 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 15.79% 0.907491 -0.279332 1.684638 0.884186 0.885119 0.856075 0.955164 -0.233047 0.8277 0.7176 0.4892 2.264774 2.076999
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 0.00% 0.00% 0.00% 0.00% 1.07% 0.00% 1.357772 -0.117737 0.692816 0.544481 1.898464 3.082918 2.757303 2.047856 0.8009 0.7540 0.3653 2.332825 2.112866

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 54: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Power 29.735184 0.505495 13.290354 -0.618168 29.735184 2.109279 14.331254 3.996132 2.330787

Antenna 54: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Power 27.761044 -0.442216 15.366130 -0.414620 27.761044 1.858237 21.827506 1.449361 0.797086

Antenna 54: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Power 33.721827 24.867707 -1.075278 33.721827 -0.007132 21.664346 1.615530 4.256981 -0.512638

Antenna 54: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Power 39.432344 -0.315897 16.905537 0.139502 39.432344 -0.204663 10.115741 0.307908 1.564699

Antenna 54: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Shape 13.915515 13.915515 0.504969 5.904540 0.152813 0.808160 0.454357 6.230232 1.493963

Antenna 54: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Temporal Variability 64.463905 -0.975150 17.085871 -1.175527 19.115369 0.196363 64.463905 1.592351 0.231233

Antenna 54: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Temporal Discontinuties 772.492363 84.055899 67.892118 66.768911 71.443569 67.519417 68.429362 591.556943 772.492363

Antenna 54: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Temporal Discontinuties 1.390399 -0.789290 0.845383 0.569532 0.815562 0.352991 -0.544486 1.390399 0.432844

Antenna 54: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 11.433258 1.596226 11.433258 0.992896 -0.579345 0.533210 9.220807 0.789468 1.014506

Antenna 54: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Power 1.343212 -0.531910 -0.549216 -1.052095 1.343212 -0.668479 -0.895905 -0.206040 0.774682

Antenna 54: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 22.870577 1.580126 22.870577 1.387894 1.288152 0.789526 5.660819 1.275403 2.703064

Antenna 54: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 35.378165 35.378165 0.887994 1.168500 1.133631 4.816593 0.949517 2.038527 1.734312

Antenna 54: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 11.643199 11.643199 0.866973 1.823077 1.028494 3.400357 0.059000 0.119643 2.502953

Antenna 54: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 26.744552 0.465320 26.744552 1.336424 1.512398 0.645341 3.833578 0.127570 0.623499

Antenna 54: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 15.447347 15.447347 1.357972 2.287286 1.626663 5.727232 1.295870 -0.082438 0.563729

Antenna 54: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Temporal Discontinuties 15.917780 6.352998 0.595436 0.424943 1.364107 7.217102 -0.965889 15.917780 -0.584822

Antenna 54: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 28.965965 0.568712 28.965965 1.229012 0.985292 0.224002 2.603130 1.311546 0.107834

Antenna 54: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 6.588890 6.588890 0.168314 3.457562 1.941136 3.290488 0.094130 1.683441 2.220261

Antenna 54: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape 8.403356 0.914717 8.403356 1.392426 3.117768 -0.513406 5.749390 0.976564 7.216219

Antenna 54: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Temporal Discontinuties 24.437464 1.898634 1.481911 1.798883 1.325956 3.371661 -1.375839 24.437464 0.215494

Antenna 54: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Temporal Variability 11.202453 0.443531 2.954496 1.131213 1.142228 0.300717 11.202453 0.492268 4.520073

Antenna 54: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Power 1.319126 0.837481 -0.306333 1.319126 1.057010 -0.334606 -0.447355 -0.254084 -0.719210

Antenna 54: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Power 1.846962 -0.685763 0.657856 0.832313 1.846962 1.487681 0.967530 -0.570147 1.246738

Antenna 54: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok ee Power 1.684638 -0.279332 0.907491 0.884186 1.684638 0.856075 0.885119 -0.233047 0.955164

Antenna 54: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 54: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
54 N04 digital_ok nn Temporal Variability 3.082918 -0.117737 1.357772 0.544481 0.692816 3.082918 1.898464 2.047856 2.757303
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